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MCP server for developers adding human review gates, prompt risk checks, FAQ review, and CRM note safety to AI tools.","maintainers":[{"name":"miraigent","email":"info@miraigent.com"}],"readme":"# Miraigent Free AI Ops MCP\n\nFree public Model Context Protocol (MCP) server for human-reviewed AI\noperations.\n\nUse it when you are building an AI tool, MCP server, support workflow, or\ninternal automation that needs a visible human-review gate before AI output\nreaches customers or shared systems.\n\n## Try It In 30 Seconds\n\nRun the public MCP server:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n\nThen send a JSON-RPC tool call such as the copy-ready example in\nexamples/human-review-gate/.\n\nFor a complete public-safe MCP session that covers initialize, tools/list, and\none tool call, see examples/mcp-json-rpc-session/.\n\nIf you only want to confirm which tools the server exposes before sending any\nsample tool-call input, use examples/tools-list-json-rpc-session/.\n\nIf your first concern is whether a customer-facing prompt should be stopped\nbefore AI use, use examples/prompt-risk-json-rpc-session/ for a copy-ready\nprompt_risk_review session.\n\nIf your first concern is whether a repeated support question belongs in a public\nFAQ, internal FAQ, or human-review rule, use\nexamples/faq-candidate-review-json-rpc-session/ for a copy-ready\nfaq_candidate_review session.\n\nIf your first concern is separating customer facts, AI suggestions, human\ndecisions, and next actions before a note goes into a CRM, use\nexamples/ai-safe-crm-note-json-rpc-session/ for a copy-ready ai_safe_crm_note\nsession.\n\nThat JSON-RPC session is also covered by `npm test`, so the README proof path\nand packaged example stay aligned when the MCP response shape changes.\n\n## One-Command Public Smoke Test\n\nUse this when you want to confirm the npm package works before editing a desktop\nMCP client config:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/mcp-json-rpc-session/sample-session.jsonl\n\nThe response should include:\n\n- serverInfo.name: miraigent-free-ai-ops-mcp\n- tools/list with four tools\n- human_review_gate returning `stop` for the synthetic refund/complaint/personal\n  data example\n\nThis is the fastest public proof path for npm and GitHub users. If the command\nstarts but the returned status is confusing, open a Tried It feedback issue with\nthe command, synthetic input shape, and returned status only.\n\nTo inspect the public tool list without running any tool call:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/tools-list-json-rpc-session/sample-session.jsonl\n\nThat response should include `human_review_gate`, `faq_candidate_review`,\n`ai_safe_crm_note`, and `prompt_risk_review`.\n\nTo print only the public tool names from that `tools/list` response without\ncopying a full MCP client log, parse the final JSON-RPC line with Node:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/tools-list-json-rpc-session/sample-session.jsonl | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); console.log(r.result.tools.map(t => t.name).join(\"\\n\")); })'\n\nThat prints four lines: `human_review_gate`, `faq_candidate_review`,\n`ai_safe_crm_note`, and `prompt_risk_review`.\n\nIf you have not cloned the repository and only want the packaged public tool\nnames, run the same check from a temporary directory and stream the tools-list\nsample out of the npm tarball:\n\n    workdir=$(mktemp -d) && trap 'rm -rf \"$workdir\"' EXIT && cd \"$workdir\" && pkg=$(npm pack --silent @miraigent/free-ai-ops-mcp@latest) && tar -xOf \"$pkg\" package/examples/tools-list-json-rpc-session/sample-session.jsonl | npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); console.log(r.result.tools.map(t => t.name).join(\"\\n\")); })'\n\nThat clone-free tools-list check prints only the four public tool names and\nremoves the downloaded tarball with the temporary directory cleanup trap.\n\nIf that tools-list check passes, the next safest tool-call check is the bundled\n`human_review_gate` session:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/mcp-json-rpc-session/sample-session.jsonl\n\nThat sample uses only synthetic refund, complaint, and personal-data flags, and\nshould return `gateStatus: \"stop\"`. Use this step to confirm tool-call output\nbefore pasting any real workflow data into an MCP client.\n\nTo confirm the FAQ review output shape before you create a public issue or FAQ\ndraft, run the bundled `faq_candidate_review` session:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/faq-candidate-review-json-rpc-session/sample-session.jsonl\n\nThe final response should include `recommendedStatus: \"public_faq_candidate\"`\nfor the synthetic pricing-plan question. Report only the repeated question\npattern, risk level, and returned `recommendedStatus`; do not paste support\ninbox exports or private policy text.\n\nFor maintainers and contributors, `npm test` replays the same public\n`examples/mcp-json-rpc-session/sample-session.jsonl` file and checks the\nreturned server name, version, tool count, and review-gate fields.\n\nIf you are checking the package from npm search, run the public help first:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp --help\n\nThe help output lists the available MCP tools, the one-command smoke test, and\nthe public-safe boundary before you send any JSON-RPC input. The first line\nalso prints `Miraigent Free AI Ops MCP <version>`, which is the quickest way to\nconfirm whether `npx` is using the current public package or a stale local\ncache.\n\nIf a local npx cache or desktop MCP client appears stale, compare it with the\npublic registry version before changing private client configuration:\n\n    npm view @miraigent/free-ai-ops-mcp version\n\nThe version printed by `npm view` should match the version shown in the package\nhelp output and in the MCP `initialize` response.\n\nQuick version mismatch check:\n\n1. Run `npm view @miraigent/free-ai-ops-mcp version`.\n2. Run `npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp --help` and\n   confirm the header shows the same version.\n3. Run the one-command smoke test and confirm the `initialize` response includes\n   the same `serverInfo.version`.\n\nIf only the desktop MCP client shows an older version after those checks pass,\nrestart the client and re-check its `command` and `args` path before changing\nany private workflow data.\n\nQuick initialize response check:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/mcp-json-rpc-session/sample-session.jsonl | head -n 1\n\nThat first response should include `protocolVersion: \"2024-11-05\"`,\n`capabilities.tools`, and `serverInfo.version`. If those fields appear in the\nterminal but not in a desktop MCP client, debug the client restart/config path\nbefore changing private workflow data.\n\nIf the result is unclear, open a Tried It feedback issue with synthetic input\nonly. A useful issue can be as small as:\n\n- the tool you ran\n- the returned status or field that was confusing\n- the review rule, risk flag, or example that would make the next run easier\n\nhttps://github.com/Miraigent/miraigent-free-ai-ops-mcp/issues/new?template=tried_it_feedback.md\n\nIf you are not a developer and only want the spreadsheet/checklist version after\nseeing the MCP example, download the free review kit:\n\nhttps://miraigent.gumroad.com/l/human-review-gate-ai-drafts?utm_source=github&utm_medium=readme&utm_campaign=free-ai-ops-mcp-013\n\n## Use With Claude Desktop or Cursor\n\nAdd to your `claude_desktop_config.json` or Cursor MCP settings:\n\n    {\n      \"mcpServers\": {\n        \"miraigent-free-ai-ops-mcp\": {\n          \"command\": \"npx\",\n          \"args\": [\"-y\", \"free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\"]\n        }\n      }\n    }\n\nAfter restarting Claude Desktop or Cursor, the four tools\n(`human_review_gate`, `faq_candidate_review`, `ai_safe_crm_note`,\n`prompt_risk_review`) will be available in the MCP tools panel.\n\nBefore connecting a real workflow, try one synthetic `human_review_gate` call in\nyour MCP client and compare the input shape with this public example:\n\n    {\n      \"draftType\": \"support reply\",\n      \"audience\": \"customer\",\n      \"riskFlags\": [\"refund\", \"personal data\"],\n      \"reviewOwner\": \"support lead\",\n      \"sendMode\": \"manual\"\n    }\n\nFor that kind of input, the expected result is `stop` or `review_required`, plus\na boundary note saying the tool does not send messages. If your client shows a\ndifferent field name or hides the returned status, open a Tried It feedback\nissue with synthetic input only.\n\nClaude Desktop config location:\n\n- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`\n- Windows: `%APPDATA%\\Claude\\claude_desktop_config.json`\n\n## MCP Client Troubleshooting Checklist\n\nIf the package runs from the terminal but does not appear inside Claude Desktop,\nCursor, or another MCP client, check the connection in this order:\n\n- Run `npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp --help` in the\n  same shell account that launches the MCP client.\n- Confirm the client config uses `command: \"npx\"` and the exact args shown in\n  this README.\n- Restart the MCP client after saving the config. Most desktop clients read MCP\n  server config only on startup.\n- Run the one-command smoke test with the public JSON-RPC session before\n  changing private workflows.\n- If `tools/list` works in the terminal but not in the client, open a Tried It\n  feedback issue with the client name, operating system, command shape, and the\n  returned public-safe status fields.\n\nIf a tool call returns `Unknown tool: <name>`, treat it as a tool-name mismatch\nfirst. Re-run the tools-list check, compare the requested name with the four\npublic tool names, and report only the command shape, requested synthetic tool\nname, request id, and returned `error.message`. Do not paste private client logs\nor workflow data to explain the mismatch.\n\nDo not paste real customer records, secrets, internal policy text, paid product\nfiles, or private memory behavior into client logs or GitHub issues.\n\n## What Success Looks Like\n\nUse this quick check before connecting private systems or opening an issue:\n\n- The MCP client starts `miraigent-free-ai-ops-mcp` without credentials.\n- `tools/list` shows four public alpha tools:\n  `human_review_gate`, `faq_candidate_review`, `ai_safe_crm_note`, and\n  `prompt_risk_review`.\n- A support-reply review returns one of `auto_ok`, `review_required`, or\n  `stop`, plus a `boundary` note that confirms the package does not send\n  messages.\n- A prompt review returns `proceed_with_checklist`,\n  `human_review_required`, or `stop_before_ai_use` before any real customer\n  data is used.\n\nIf one of those checks fails, open a Tried It feedback issue with the command\nyou ran, the public-safe input shape, and the returned status field. Do not\npaste private customer records, secrets, internal policy text, or paid product\nfiles.\n\n## Read The Returned Status\n\nAfter the smoke test runs, look for the status field from the tool you called\nbefore changing client configuration or private workflows.\n\nQuick field map:\n\n- `human_review_gate`: read `gateStatus`.\n- `faq_candidate_review`: read `recommendedStatus`.\n- `ai_safe_crm_note`: read `crmNote.nextAction` and the `maskingChecklist`.\n- `prompt_risk_review`: read `recommendation` and `riskFlags`.\n\nThose fields are returned inside MCP `content[0].text`, so parse that wrapped\ntext as JSON before deciding whether the next action is proceed, review, or\nstop.\n\nIn raw JSON-RPC output, MCP wraps each tool result inside `content[0].text`.\nParse that text value as JSON before you check the returned decision:\n\n    const response = JSON.parse(lineFromStdout);\n    const toolResult = JSON.parse(response.result.content[0].text);\n    console.log(toolResult.gateStatus);\n\nFor the bundled smoke-test session, that prints `stop`. Use the parsed\n`gateStatus`, `recommendation`, or `recommendedStatus` field from the relevant\ntool before changing a desktop MCP client config or connecting private data.\n\nIf you only need a terminal check, you can copy the final JSON-RPC line from the\nsmoke-test output and inspect the wrapped text field with Node:\n\n    node -e 'const r=JSON.parse(process.argv[1]); console.log(JSON.parse(r.result.content[0].text));' '<paste one response line here>'\n\nTo avoid copying any response text at all from a repository checkout, run the\nbundled public sample and parse only its final synthetic tool-call response:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/mcp-json-rpc-session/sample-session.jsonl | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); console.log(JSON.parse(r.result.content[0].text).gateStatus); })'\n\nThat prints `stop` for the bundled support-reply example. If it does, the\npackage is returning the expected MCP result shape and you can debug client\nconfiguration separately from tool behavior.\n\nIf you have not cloned the repository, fetch the public npm tarball and stream\nthe packaged example directly into the same `npx` command:\n\n    pkg=$(npm pack --silent @miraigent/free-ai-ops-mcp@latest) && tar -xOf \"$pkg\" package/examples/mcp-json-rpc-session/sample-session.jsonl | npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n\nThat command uses only the public package contents and the synthetic bundled\nsample. Delete the downloaded `*.tgz` file after the check if you do not need it.\n\nTo keep the npm tarball check from leaving a downloaded package in your current\ndirectory, run it inside a temporary directory with a cleanup trap:\n\n    workdir=$(mktemp -d) && trap 'rm -rf \"$workdir\"' EXIT && cd \"$workdir\" && pkg=$(npm pack --silent @miraigent/free-ai-ops-mcp@latest) && tar -xOf \"$pkg\" package/examples/mcp-json-rpc-session/sample-session.jsonl | npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n\nThat variant leaves your repository checkout unchanged while still testing the\nsame packaged synthetic JSON-RPC session from npm.\n\nFor the tarball smoke test, the first response should include\n`serverInfo.name: \"miraigent-free-ai-ops-mcp\"` and the current public package\nversion. The final response should wrap a `human_review_gate` result whose\nparsed `gateStatus` is `\"stop\"` for the bundled synthetic support-reply sample.\nIf the tarball command runs but those fields differ, report the package version,\ncommand shape, and returned public status fields only.\n\nPaste only the synthetic response from the public example. Do not paste private\ncustomer records or desktop client logs into shell history, screenshots, or\nGitHub issues.\n\nFor `human_review_gate`:\n\n- `auto_ok`: the synthetic draft looks low risk, but the tool still does not\n  send anything.\n- `review_required`: keep a human reviewer in the workflow before sending.\n- `stop`: pause the workflow and resolve the sensitive, payment, complaint,\n  privacy, public-facing, or policy issue first.\n\nFor `prompt_risk_review`:\n\n- `review_checklist_required`: document the data-handling checklist before\n  running the prompt.\n- `human_review_required`: add a human review step before AI output can affect a\n  customer-facing workflow.\n- `stop_before_ai_use`: do not run the prompt until the data-handling rule is\n  reviewed.\n\nFor public `prompt_risk_review` feedback, share only the operation label,\nsanitized data-type labels, the returned `recommendation`, and the returned\n`riskFlags`. Do not paste the original prompt, customer text, internal policy,\nor private workflow logs.\n\nTo verify the prompt-risk result without copying the wrapped JSON-RPC response,\nrun the bundled public sample and print only the returned recommendation and\nrisk flags:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/prompt-risk-json-rpc-session/sample-session.jsonl | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); const result = JSON.parse(r.result.content[0].text); console.log(result.recommendation + \" \" + result.riskFlags.join(\",\")); })'\n\nThat prints `stop_before_ai_use customer_facing,sensitive_data_possible` for\nthe synthetic support-prompt example. If your prompt needs a different result,\nshare only the operation label, sanitized data-type labels, recommendation, and\nrisk flags in a public issue.\n\nFor public `ai_safe_crm_note` feedback, share only a masked note label, channel,\nwhether personal data was present, the returned `crmNote.nextAction`, and the\nreturned `maskingChecklist` result. Do not paste the raw CRM note, customer\nmessage, contact details, internal policy, or private workflow logs.\n\nTo verify the CRM note result without copying the wrapped JSON-RPC response,\nrun the bundled public sample and print only the returned next action:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/ai-safe-crm-note-json-rpc-session/sample-session.jsonl | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); console.log(JSON.parse(r.result.content[0].text).crmNote.nextAction); })'\n\nThat prints `send setup checklist and confirm kickoff date` for the synthetic\ncontact-form example. If your CRM workflow needs a different next action, share\nonly the masked note label, channel, personal-data yes/no value, and returned\nnext action in a public issue.\n\nFor `faq_candidate_review`, use `recommendedStatus` to decide whether the\npattern belongs in a public FAQ, internal FAQ, or human-review rule. For\n`ai_safe_crm_note`, check that facts, AI suggestions, human decisions, and next\nactions stay in separate fields.\n\nTo verify the FAQ review result without copying the wrapped JSON-RPC response,\nrun the bundled public sample and print only the returned recommended status:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp < examples/faq-candidate-review-json-rpc-session/sample-session.jsonl | tail -n 1 | node -e 'process.stdin.on(\"data\", c => { const r = JSON.parse(c); console.log(JSON.parse(r.result.content[0].text).recommendedStatus); })'\n\nThat prints `public_faq_candidate` for the synthetic pricing-plan question. If\nyour repeated-question workflow needs a different status, share only the\nquestion-pattern label, risk level, expected status, and returned\n`recommendedStatus` in a public issue.\n\nIf the status is surprising, open a Tried It feedback issue with synthetic input\nonly. The most useful report says which status you expected, which status you\nreceived, and what extra rule or explanation would have made the result easier\nto use.\n\n## Copy A Useful Feedback Result\n\nWhen you open a Tried It feedback issue, the most useful report is the smallest\npublic-safe result shape that shows where the review gate helped or felt unclear.\n\nGood public-safe issue body:\n\n    Command: npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n    Tool: human_review_gate\n    Input shape:\n      draftType: customer support reply\n      audience: customer\n      riskFlags: refund; complaint; personal data\n      sendMode: manual\n    Returned status: stop\n    Confusing part: I expected review_required, but stop may be correct because refund and personal data were both present.\n    Requested improvement: Add one sentence explaining why stop is stronger than review_required.\n\nKeep the report synthetic. Replace names, emails, customer text, internal policy\ntext, and private CRM notes with short labels before posting.\n\n## Who This Helps\n\n- Developers adding review gates to AI agents or MCP tools.\n- Indie hackers building support, FAQ, CRM, or prompt-review utilities.\n- AI automation builders who need a safe stop/review/approve step.\n- Teams prototyping human-in-the-loop AI workflows before integrating real data.\n- Operators who can run npm/npx and want a small public MCP example.\n\n## Pick Your First Tool\n\nStart with the tool that matches the first unsafe handoff in your workflow:\n\n- AI draft may reach a customer: use `human_review_gate`.\n- Repeated support questions should become a public FAQ: use\n  `faq_candidate_review`.\n- CRM notes mix facts, AI suggestions, and human decisions: use\n  `ai_safe_crm_note`.\n- A prompt may touch customer data or public output: use `prompt_risk_review`.\n\nCopy-ready examples:\n\n- Human review gate: `npm run example:human-review-gate`\n- FAQ candidate review: `npm run example:faq-candidate-review`\n- AI-safe CRM note: `npm run example:ai-safe-crm-note`\n- AI-safe CRM note JSON-RPC session:\n  `npm run mcp < examples/ai-safe-crm-note-json-rpc-session/sample-session.jsonl`\n- Prompt risk review: `npm run example:prompt-risk-review`\n- Prompt risk JSON-RPC session:\n  `npm run mcp < examples/prompt-risk-json-rpc-session/sample-session.jsonl`\n\nAll examples use synthetic data. Keep private customer records, secrets,\ninternal policy text, and paid product files out of public issues and screenshots.\n\n## What To Do Next\n\n- Try one tool with synthetic data.\n- If you ran `npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp`, paste the public-safe result\n  shape into the Tried It feedback issue.\n- Share what happened in the Tried It feedback issue if setup, JSON-RPC input,\n  or the returned gate decision was unclear.\n- Open a workflow request if a risk flag, status, or output field is missing.\n- Use the Gumroad kit after the MCP example if you want CSV/checklist files\n  instead of npm.\n- Adapt the review-gate fields before connecting private systems or real users.\n\nIssue entry points:\n\n- Tried It feedback: https://github.com/Miraigent/miraigent-free-ai-ops-mcp/issues/new?template=tried_it_feedback.md\n- Workflow request: https://github.com/Miraigent/miraigent-free-ai-ops-mcp/issues/new?template=free_mcp_candidate_request.md\n- Bug report: https://github.com/Miraigent/miraigent-free-ai-ops-mcp/issues/new?template=free_mcp_bug_report.md\n\n## Alpha Tools\n\n- human_review_gate: decide whether an AI draft should be sent, reviewed, or stopped.\n- faq_candidate_review: turn repeated inquiry patterns into FAQ candidates.\n- ai_safe_crm_note: structure CRM notes without mixing facts, AI suggestions, and human decisions.\n- prompt_risk_review: review an AI prompt or task before it is used in operations.\n\nThese tools are public alpha candidates. Please use GitHub issues for bugs,\nunclear outputs, missing fields, and safe public use cases:\n\nhttps://github.com/Miraigent/miraigent-free-ai-ops-mcp/issues/new/choose\n\n## Start With One Review Gate\n\nThe first practical use case is a review gate for AI-drafted customer replies.\nBefore a team lets an AI draft leave a help desk, inbox, form workflow, or CRM,\nthe tool separates three outcomes:\n\n- auto_ok: low-risk internal or routine copy can continue.\n- review_required: a human should review the draft before it is sent.\n- stop: sensitive, legal, payment, complaint, privacy, or public-facing risks\n  should be handled by a person before AI-assisted sending continues.\n\n### Quick MCP Example\n\nExample input:\n\n    {\n      \"draftType\": \"customer support reply\",\n      \"audience\": \"customer\",\n      \"riskFlags\": [\"refund\", \"complaint\", \"personal data\"],\n      \"reviewOwner\": \"support lead\",\n      \"sendMode\": \"manual\"\n    }\n\nExpected result:\n\n    {\n      \"gateStatus\": \"stop\",\n      \"reviewOwner\": \"support lead\",\n      \"boundary\": \"This tool is a review helper. It does not send messages.\"\n    }\n\nUse this as a small public proof before building a larger AI support workflow.\n\nSee examples/human-review-gate/ for copy-ready JSON-RPC examples and a sample\ndecision log that match the free Gumroad kit.\n\n## Copy-Ready MCP Session\n\nUse this when you want to confirm the package responds like an MCP server before\nconnecting it to Claude Desktop, Cursor, or your own MCP client:\n\n    npm run mcp < examples/mcp-json-rpc-session/sample-session.jsonl\n\nThe session sends three JSON-RPC messages:\n\n- initialize: confirms protocolVersion, capabilities, and serverInfo.\n- tools/list: confirms the four public alpha tools are visible.\n- tools/call: runs human_review_gate with synthetic support-reply data.\n\nThe first response should include `protocolVersion: \"2024-11-05\"`,\n`capabilities.tools`, and a `serverInfo.version` value that matches\n`package.json` and the public npm registry version.\n\nIf you open a GitHub issue, copy only synthetic input shapes and returned status\nfields. Do not paste private customer records, secrets, tokens, internal policy\ntext, or MIRAI Memory behavior.\n\n## Check A Prompt Before AI Use\n\nUse prompt_risk_review before a support, CRM, FAQ, or workflow prompt is sent to\nAI. It helps developers decide whether a prompt can proceed with a checklist,\nneeds human review, or should stop before use because it touches sensitive data\nor customer-facing output.\n\nExample input:\n\n    {\n      \"operation\": \"support automation\",\n      \"promptSummary\": \"Draft a customer reply from inquiry details and suggest the next support step.\",\n      \"dataTypes\": [\"customer email\", \"inquiry body\", \"plan name\"],\n      \"customerFacing\": true,\n      \"riskLevel\": \"medium\"\n    }\n\nExpected result:\n\n    {\n      \"recommendation\": \"human_review_required\",\n      \"riskFlags\": [\"customer_facing\", \"sensitive_data_possible\"],\n      \"boundary\": \"This tool is a prompt risk helper. It is not legal advice and does not call an AI API.\"\n    }\n\nRun the copy-ready example:\n\n    npm run example:prompt-risk-review\n\n## Launch Flow\n\nSee LAUNCH_FLOW.md for the first public posting plan, issue collection flow, and\ndeveloper-focused distribution route.\n\n## Run\n\n    npm run mcp\n\nRun from npm:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n\nRun checks:\n\n    npm run check\n    npm test\n\nDirect JSON-RPC smoke call:\n\n    printf '%s\\n' '{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"human_review_gate\",\"arguments\":{\"draftType\":\"customer support reply\",\"audience\":\"customer\",\"riskFlags\":[\"refund\",\"complaint\",\"personal data\"],\"reviewOwner\":\"support lead\",\"sendMode\":\"manual\"}}}' | npm run mcp\n\nRun the public FREE-004 example:\n\n    npm run example:human-review-gate\n\nRun the prompt risk review example:\n\n    npm run example:prompt-risk-review\n\nRun the FAQ candidate review example:\n\n    npm run example:faq-candidate-review\n\nRun the AI-safe CRM note example:\n\n    npm run example:ai-safe-crm-note\n\nRun the AI-safe CRM note JSON-RPC session:\n\n    npm run mcp < examples/ai-safe-crm-note-json-rpc-session/sample-session.jsonl\n\n## npm Package\n\nPackage name: @miraigent/free-ai-ops-mcp\n\nCommand:\n\n    npx -y free-ai-ops-mcp@npm:@miraigent/free-ai-ops-mcp\n\n## Public Boundary\n\nThis repository may publish:\n\n- free MCP tools for reviewable AI operations\n- examples without private customer data\n- tests and issue templates\n\nThis repository must not publish:\n\n- credentials, tokens, cookies, or private keys\n- customer records\n- private company notes\n- MIRAI Memory engine details\n- working memory MCP behavior\n- full paid product files\n\n## Related Resources\n\n- Resource hub: https://miraigent.com/resources.html\n- Parent template repository: https://github.com/Miraigent/miraigent-ai-ops-templates\n- Free template library: https://miraigent.com/en/free-ai-operations-templates.html\n- Free Gumroad review kit: https://miraigent.gumroad.com/l/human-review-gate-ai-drafts?utm_source=github&utm_medium=readme&utm_campaign=free-ai-ops-mcp-013\n","readmeFilename":"README.md"}